A classifier system using smooth graph coloring
Unsupervised classifiers allow clustering methods with less or no human intervention. Therefore it is desirable to group the set of items with less data processing. This paper proposes an unsupervised classifier system using the model of soft graph coloring. This method was tested with some classic...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2017 |
| País: | Costa Rica |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Idioma: | español |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/27795 |
| Acceso en línea: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/27795 |
| Access Level: | acceso abierto |
| Palabra clave: | soft coloring unsupervised classification clustering optimization coloración suave clasificación no supervisada clasificación automática agrupación optimización |
| Sumario: | Unsupervised classifiers allow clustering methods with less or no human intervention. Therefore it is desirable to group the set of items with less data processing. This paper proposes an unsupervised classifier system using the model of soft graph coloring. This method was tested with some classic instances in the literature and the results obtained were compared with classifications made with human intervention, yielding as good or better results than supervised classifiers, sometimes providing alternative classifications that considers additional information that humans did not considered. |
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